Single-nuclei RNA-seq on human retinal tissue provides improved transcriptome profiling

Qingnan Liang, Rachayata Dharmat, Leah Owen, Akbar Shakoor, Yumei Li, Sangbae Kim, Albert Vitale, Ivana Kim, Denise Morgan, Shaoheng Liang, Nathaniel Wu, Ken Chen, Margaret M. DeAngelis () and Rui Chen ()
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Qingnan Liang: Baylor College of Medicine
Rachayata Dharmat: Baylor College of Medicine
Leah Owen: University of Utah School of Medicine
Akbar Shakoor: University of Utah School of Medicine
Yumei Li: Baylor College of Medicine
Sangbae Kim: Baylor College of Medicine
Albert Vitale: University of Utah School of Medicine
Ivana Kim: University of Utah School of Medicine
Denise Morgan: University of Utah School of Medicine
Shaoheng Liang: The University of Texas MD Anderson Cancer Center
Nathaniel Wu: Baylor College of Medicine
Ken Chen: The University of Texas MD Anderson Cancer Center
Margaret M. DeAngelis: University of Utah School of Medicine
Rui Chen: Baylor College of Medicine

Nature Communications, 2019, vol. 10, issue 1, 1-12

Abstract: Abstract Single-cell RNA-seq is a powerful tool in decoding the heterogeneity in complex tissues by generating transcriptomic profiles of the individual cell. Here, we report a single-nuclei RNA-seq (snRNA-seq) transcriptomic study on human retinal tissue, which is composed of multiple cell types with distinct functions. Six samples from three healthy donors are profiled and high-quality RNA-seq data is obtained for 5873 single nuclei. All major retinal cell types are observed and marker genes for each cell type are identified. The gene expression of the macular and peripheral retina is compared to each other at cell-type level. Furthermore, our dataset shows an improved power for prioritizing genes associated with human retinal diseases compared to both mouse single-cell RNA-seq and human bulk RNA-seq results. In conclusion, we demonstrate that obtaining single cell transcriptomes from human frozen tissues can provide insight missed by either human bulk RNA-seq or animal models.

Date: 2019
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DOI: 10.1038/s41467-019-12917-9

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